Destination prediction using text analysis

ABSTRACT

A method and device relating to destination prediction of communication messages is presented. The device may include an analyzer configured to analyze a message entered in a universal input field. The analyzer may also provide a search variable based on the entered message. The device may also include a or which may be configured to receive the search variable and determine at least one suggested destination based on the search variable. The prediction of communication destinations eliminates the need for various menus and sub-menus. Thus, a user may send a communication message without the need of lengthy navigations.

RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.12/728,771, filed on Mar. 22, 2010 (now U.S. Pat. No. 8,527,530), thedisclosure of which is incorporated herein by reference.

TECHNICAL FIELD

Example embodiments are directed towards destination prediction forcommunication devices, where a computing system may predict a desiredrecipient for a communication message. The destination predictioneliminates the need for navigation menus and decreases the time spent insending communication messages.

BACKGROUND

Mobile phones often contain a number of applications and functions.Furthermore, with today's trend towards open source technology, a mobileuser may quickly fill the capacity of a mobile phone with variousapplications. Due to the nature of mobile phones (e.g., small screensand limited input capabilities) each task a user wants to carry outtypically starts with several steps of navigation before initiating thedesired task. For example, to reach an application or perform a certainfunction a user may need to first unlock the mobile device, open a mainmenu, select an icon from the main menu, and then select an option froma sub-menu.

SUMMARY

Historically, attempts to limit the amount of user navigation haveinvolved predefined and personalized shortcuts. However, as the numberof applications and ways users communicate increase, shortcuts systemsare either not able to handle the number of applications which may beincluded in a mobile phone, or the shortcut system may be too complex tobe of any actual benefit as they eventually end up becoming a menuthemselves.

Therefore, example embodiments are directed towards destinationprediction where the need for navigation and menus are eliminated.Instead, the mobile system may be able to predict a desired applicationor recipient of a communication message in the same screen in which auser inputs a message. According to example embodiments, a communicationdesignation prediction device may include an analyzer that may beconfigured to analyze a message entered in a universal input field. Theanalyzer may be further configured to provide at least one searchvariable from the message.

The prediction device may further include a processor that may beconfigured to determine at least one suggested destination of themessage based on the at least one search variable. The processor may befurther configured to search through a database of a user'scommunication history, where the search may be based on the at least onesearch variable. The processor may be further configured to determinethe at least one suggested destination based on at least one occurrencein the communication history. The at least one occurrence may be, forexample, a frequent or recent occurrence in the user's communicationhistory. The processor may also be configured to adaptively update thecommunication history based on a current interaction. The at least onedestination may be, for example, an application, a service, or a contactentry. The at least one search variable may be, for example, an actionword or a recognized contact.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing will be apparent from the following more particulardescription of the example embodiments, as illustrated in theaccompanying drawings in which like reference characters refer to thesame parts throughout the different views. The drawings are notnecessarily to scale, emphasis instead being placed upon illustratingthe example embodiments.

FIGS. 1A-1F are screen captions employing example embodiments; and

FIG. 2 is a block diagram of a designation prediction device accordingto example embodiments.

DETAILED DESCRIPTION

In the following description, for purposes of explanation and notlimitation, specific details are set forth, such as particularcomponents, elements, techniques, etc. in order to provide a thoroughunderstanding of the example embodiments. However, it will be apparentto one skilled in the art that the example embodiments may be practicedin ways which may depart from these specific details. In otherinstances, detailed descriptions of well-known methods and elements areomitted so as not to obscure the description of the example embodiments.

FIGS. 1A-1F illustrate an example screen captions 100, and FIG. 2illustrates a communication designation prediction device 200 accordingto example embodiments.

In FIG. 1A, the screen caption 100 includes a universal input field 102where user input may be entered. Above the universal input field 102, alist of potential message recipients 104 may be included. Initially,before any data has been entered in the universal input field 102, therecipient list may comprise a default of any number of frequent messagerecipients from a contact list 106 and/or frequently used applications108 that may be resident on and/or associated with a communicationdevice. It should be appreciated that the default list may be determinedadaptively and/or dynamically based on the user's communication history,a user's activity history, and/or the user may have the ability to editthe default list. The screen caption 100 may also include a find option110 where a user may search through a list of applications and/orcontact recipients, for example, through the use of menus in any mannerknown in the art.

FIG. 1B depicts the entry of user data 112 in the universal input field102. An analyzer 204 of the communication destination prediction device200 may be configured to continuously monitor the universal input field102 for input, for example, per character or other particular parseableportion of data. Therefore, upon data 112 being entered in the inputfield 102, the data 112 and/or portions thereof may be immediately sentto the analyzer 204. The analyzer 204 may be configured to look for anumber of “action words.” In the example provided in FIG. 1B, the word‘Hi’ may be identified as an action word. Typically, emails and/or text(e.g., SMS) messages begin with the word ‘Hi’; therefore, the analyzer204 may be programmed to identify the word ‘Hi’ as an action word, forexample, if the word is the first word input in the universal inputfield 102. It should be appreciated that the analyzer 204 may beadaptively trained to search for action words based on a user's historyand/or the analyzer 204 may be programmed by the user and/ormanufacturer. It should further be appreciated that an action word maytake on other forms. For example, an action word may be a name of anapplication or a contact stored in a contact database associated with acommunication device.

In the example provided by FIG. 1B, the analyzer 204 may provide theaction word 206 ‘Hi’ to the processor 208. The processor 208 may in turnuse the action word as a search variable 210 to perform a search of adatabase 209, for example, of a user's communication history. In thepresent example, the processor may search for frequently and/or recentlyemailed and/or texted recipients. The database 209 may return searchresults 212 based on at least one occurrence in the user history back tothe processor 208, where the processor 208 may return a suggesteddestination list 104 to the display screen associated with acommunication device.

It should be appreciated that the processor 208 may be configured tocontinuously provide suggested destinations 104 as the data 112 enteredinto the universal input field 102 is entered and/or altered. Forexample, in FIG. 1C, the analyzer 204 may detect entry of a secondaction word, ‘game,’ in the universal input fiend 102. The analyzer 204may forward a second search variable 206 based on the second detectedaction word (or a combination of the first and second detected actionwords) to the processor 208, which in turn may perform a second searchof the database 209 for frequent and/or recent occurrences associatedwith the second search variable 206. In the example provided by FIG. 1C,the database may provide a second search result 212 including contactswhich have been frequently and/or recently emailed and/or texted, withthe subject of the email relating to a game. The processor 209 may thenprovide an updated suggested destination list 104 (e.g., a modifiedprevious suggested destination list) to the display screen 100. At anytime, a user may select a contact from the suggested destination list104, as shown by a (shadowed) fingerprint 114. The selected contact mayappear in a subsequent destination list 104, for example, with acheck-marked logo 116 or other (e.g., visual) identifier. The processor208 may continue to suggest additional destinations 104 even though aparticular destination has been selected, as shown in FIG. 1D. In someembodiments, subsequent suggested destination lists may be formulatedbased at least in part on the user-selected destination. In other words,relational groupings of particular destinations may be used to constructa particular suggested destination list 104. The user may also have theoption to manually search for a communication destination using thesearch option 110.

Once a destination has been selected, a user may be presented the optionto send the message 118. Upon sending the message, the processor 208 maysend information relating to the recent occurrence 214 to the database209. In the current example, search variables ‘Hi’ and ‘game’ may beindexed in the database along with the chosen destinations orrecipients. Therefore, the user communication history may becontinuously updated and adapted to a particular user. Thus, theaccuracy of the suggested destination list 104 may improve overtime.

It should be appreciated that action words may also be names. Forexample, if a user types ‘Hi Dave’ into the input field, the analyzermay identify the words ‘Hi’ and ‘Dave’ as action words. Furthermore, theprocessor may be configured to search for common nicknames and/oralternatives based on the action words. Specifically, the processor maysearch the communication history database with the search variables‘Dave’ and variants thereof, such as ‘David.’ The returned searchresults in this instance may be all entries in the user's contact listhaving names similar to Dave and/or variants thereof, e.g., David.

It should further be appreciated that in addition to a communicationhistory of the user, the processor may also be configured to searchand/or determine a suggested destination based on a user's activityhistory. For example, if a user has recently looked at status updatesthrough a mobile browser, the processor may be more likely to determinethe suggested destination as an application providing status updates.Additionally, if a user has recently viewed a photograph included atagged user; the processor may determine an increased likelihood of thecurrent user communicating with the tagged user.

It should also be appreciated that the suggested destination may also bean application, as shown in the example provided in FIG. 1E. In FIG. 1E,the analyzer 204 may receive or monitor text 112 entered into theuniversal input field 102. In the current example, the analyzer 204 maydetermine that the word ‘Is’ is an action word. The analyzer 204 maysend the determined action word as a search variable 206 to theprocessor 208. The processor may then search through the usercommunication history in database 209. A search result 212 based on atleast one occurrence may be returned to the processor 208. Based on thesearch result, the processor 208 may then send a suggested destinationlist 104 to the display screen 100. In the current example, thesuggested destination list 104 comprises two applications Facebook® andTwitter®. Many users typically enter Facebook® and Twitter® updatesstarting with the word ‘is,’ therefore, the user communication historymay indicate frequent destinations associated with the word ‘is.’

FIG. 1F provides yet another example of embodiments of the presentinvention. In FIG. 1F, the analyzer 204 may determine the action word tobe ‘Buy,’ based on this action word, the suggested destination list 104may include a contact or a note to serve as a reminder to the user. Itshould be appreciated that the predicted destination may be a specificservice provided by an application. For example, the application may bean email and the different services may include posting to a blog orcommunicating with a person. The predicted destinations may be afunction of the user's communication history, activity history, and/orany predefined settings that may be implemented. It should beappreciated that action words may be determined based on any number offactors, for example, words (including names), case, order of words,disposition, syntax, phrasing, particular weighting, selecteddestinations, destination groups, etc.

The above mentioned and described embodiments are only given as examplesand should not be limiting to the present invention. Other solutions,uses, objectives, and functions within the scope of the invention asclaimed in the below described patent claims should be apparent for theperson skilled in the art.

Furthermore, the various embodiments of the present invention describedherein is described in the general context of method steps or processes,which may be implemented in one embodiment by a computer programproduct, embodied in a computer-readable medium, includingcomputer-executable instructions, such as program code, executed bycomputers in networked environments. A computer-readable medium mayinclude removable and non-removable storage devices including, but notlimited to, Read Only Memory (ROM), Random Access Memory (RAM), compactdiscs (CDs), digital versatile discs (DVD), etc. Generally, programmodules may include routines, programs, objects, components, datastructures, etc. that perform particular tasks or implement particularabstract data types. Computer-executable instructions, associated datastructures, and program modules represent examples of program code forexecuting steps of the methods disclosed herein. The particular sequenceof such executable instructions or associated data structures representsexamples of corresponding acts for implementing the functions describedin such steps or processes.

Software and web implementations of various embodiments of the presentinvention can be accomplished with standard programming techniques withrule-based logic and other logic to accomplish various databasesearching steps or processes, correlation steps or processes, comparisonsteps or processes and decision steps or processes. It should be notedthat the words “component” and “module,” as used herein and in thefollowing claims, is intended to encompass implementations using one ormore lines of software code, and/or hardware implementations, and/orequipment for receiving manual inputs.

What is claimed is:
 1. A method comprising: determining, by a device, asearch variable based on text entered via an input field provided via adisplay of the device; determining, by the device and based on thesearch variable, a group of applications for transmitting the text fromthe device; providing, by the device, information identifying the groupof applications via the display, the information identifying the groupof applications being displayed in conjunction with the input field;receiving, by the device, a selection of an application included in thegroup of applications; and using, by the device, the application totransmit the text from the device based on the selection.
 2. The methodof claim 1, the method further comprising: receiving additional textentered via the input field; determining, based on the additional text,another search variable; determining, based on the other searchvariable, a group of contacts, of a plurality of contacts, associatedwith a user of the device, at least one contact, of the plurality ofcontacts, not being included in the group of contacts; and providinginformation identifying the group of contacts via the display, theinformation identifying the group of contacts being displayed inconjunction with the information identifying the group of applicationsand the input field.
 3. The method of claim 2, further comprising:receiving a selection of a contact included in the group of contacts;and where using the application to transmit the text includes: using theapplication to transmit the text to a device associated with theselected contact.
 4. The method of claim 1, where determining the groupof applications includes: determining that the search variable isassociated with transmitting messages from the device, determining oneor more applications that a user of the device has used to transmit amessage from the device, and determining, based on the one or moreapplications that the user of the device has used to transmit a messagefrom the device, the group of applications for transmitting the textfrom the device.
 5. The method of claim 4, where determining the one ormore applications includes: determining, based on a communicationhistory associated with the user, a quantity of times that eachapplication, of a plurality of applications, has been used fortransmitting messages from the device, the plurality of applicationsincluding the one or more applications, and determining the one or moreapplications based on the quantity of times each application has beenused to transmit the messages from the device.
 6. The method of claim 1,the method further comprising: searching a communication history of auser of the device; determining, based on searching the communicationhistory, a quantity of communications transmitted between the user andeach contact of a plurality of contacts associated with the user; andproviding, based on the quantity of communications, informationidentifying one or more contacts, of the plurality of contacts, via thedisplay.
 7. The method of claim 1, where determining the group ofapplications includes: determining that the search variable isassociated with a particular type of application, and determining thatthe group of applications are associated with the particular type ofapplication.
 8. A device comprising: a processor to: determine a searchvariable based on text entered via an input field provided via a displayassociated with the device; determine, based on the search variable, agroup of applications for transmitting the text from the device; provideinformation identifying the group of applications via the display, theinformation identifying the group of applications being displayed inconjunction with the input field; receive a selection of an applicationincluded in the group of applications; and cause, based on theselection, the application to transmit the text from the device.
 9. Thedevice of claim 8, where the processor is further to: receive additionaltext entered via the input field; determine, based on the additionaltext, another search variable; determine, based on the other searchvariable, a group of contacts, of a plurality of contacts, associatedwith a user of the device, at least one contact, of the plurality ofcontacts, not being included in the group of contacts; and provideinformation identifying the group of contacts via the display, theinformation identifying the group of contacts being displayed inconjunction with the information identifying the group of applicationsand the input field.
 10. The device of claim 9, where the processor isfurther to: receive a selection of a contact included in the group ofcontacts; and where, when causing the application to transmit the text,the processor is to: cause the application to transmit the text toanother device, the other device being associated with the selectedcontact.
 11. The device of claim 8, where, when determining the group ofapplications, the processor is to: determine that the search variable isassociated with transmitting messages from the device, determine one ormore applications that a user of the device has used to transmit amessage from the device, and determine, based on the one or moreapplications that the user of the device has used to transmit a messagefrom the device, the group of applications for transmitting the textfrom the device.
 12. The device of claim 11, where, when determining theone or more applications, the processor is to: determine, based on acommunication history associated with the user, a quantity of times thateach application, of a plurality of applications, has been used fortransmitting messages from the device, the plurality of applicationsincluding the one or more applications, and determine the one or moreapplications based on the quantity of times each application has beenused to transmit the messages from the device.
 13. The device of claim8, where the processor is further to: search a communication history ofa user of the device; determine, based on searching the communicationhistory, a quantity of communications transmitted between the user andeach contact, of a plurality of contacts associated with the user; andprovide, based on the quantity of communications, informationidentifying one or more contacts of the plurality of contacts via thedisplay.
 14. The device of claim 8, where, when determining the group ofapplications, the processor is to: determine that the search variable isassociated with a particular type of application, and determine that thegroup of applications are associated with the particular type ofapplication.
 15. A non-transitory computer-readable medium storinginstructions, the instructions comprising: one or more instructionsthat, when executed by a processor of a device, cause the processor to:determine a search variable based on text entered via an input fieldprovided via a display of the device; determine, based on the searchvariable, a group of applications for transmitting the text from thedevice; provide information identifying the group of applications viathe display, the information identifying the group of applications beingdisplayed in conjunction with the input field; receive a selection of anapplication included in the group of applications; and cause, based onthe selection, the application to transmit the text from the device. 16.The non-transitory computer-readable medium of claim 15, where theinstructions further comprise: one or more instructions that, whenexecuted by the processor, cause the processor to: receive additionaltext entered via the input field; determine, based on the additionaltext, another search variable; determine, based on the other searchvariable, a group of contacts, of a plurality of contacts, associatedwith a user of the device, at least one contact, of the plurality ofcontacts, not being included in the group of contacts; and provideinformation identifying the group of contacts via the display, theinformation identifying the group of contacts being displayed inconjunction with the information identifying the group of applicationsand the input field.
 17. The non-transitory computer-readable medium ofclaim 16, where the instructions further comprise: one or moreinstructions that, when executed by the processor, cause the processorto: receive a selection of a contact included in the group of contacts;and where, when causing the application to transmit the text, theprocessor is to: cause the application to transmit the text to anotherdevice, the other device being associated with the selected contact. 18.The non-transitory computer-readable medium of claim 15, where the oneor more instructions to determine the group of applications include: oneor more instructions that, when executed by the processor, cause theprocessor to: determine that the search variable is associated withtransmitting messages from the device, determine one or moreapplications that a user of the device has used to transmit a messagefrom the device, and determine, based on the one or more applicationsthat the user of the device has used to transmit a message from thedevice, the group of applications for transmitting the text from thedevice.
 19. The non-transitory computer-readable medium of claim 15,where the instructions further comprise: one or more instructions that,when executed by the processor, cause the processor to: search acommunication history of a user of the device; determine, based onsearching the communication history, a quantity of communicationstransmitted between the user and each contact, of a plurality ofcontacts associated with the user; and provide, based on the quantity ofcommunications, information identifying one or more contacts of theplurality of contacts via the display.
 20. The non-transitorycomputer-readable medium of claim 15, where, when determining the groupof applications, the processor is to: determine that the search variableis associated with a particular type of application, and determine thatthe group of applications are associated with the particular type ofapplication.